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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xiaoxia Dai Qiqing Zhang Jiyang Dong Zhong Chen Changqin Liu Shuyu Yang |
| Copyright Year | 2008 |
| Description | Author affiliation: Res. Center of Biomed. Eng., Xiamen Univ., Xiamen (Xiaoxia Dai; Qiqing Zhang) |
| Abstract | $^{1}H$ NMR-based metabonomics has shown considerable potential as a means of rapidly detecting and characterizing a myriad of metabolic components. The $^{1}H$ NMR spectra obtained for human urine samples were visually inspected and analyzed using principal component analysis (PCA). Urine samples were collected eight times daily (8:00, 10:00, 12:00, 14:00,18:00, 20:00) from healthy volunteers with a standard diet and lifestyle for 2 consecutive days. Separation of urinary data according to time of sampling collection was achieved. The fluctuations of creatinine, citrate and observed between urine samples collected during the different time of day may be related to hormone levels. In addition, gender-difference was also investigated and the PCA score plots revealed several metabolites that were considered significant for distinguishing between male and female: creatinine, glycine and citrate. These results showed the value of metabonomic methods in the investigation of physiological variation and rhythms, and provided suggestions to collect significative metabonomics data in clinical studies. |
| Starting Page | 2240 |
| Ending Page | 2243 |
| File Size | 228347 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424417476 |
| DOI | 10.1109/ICBBE.2008.891 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-05-16 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Drugs Spectroscopy Humans Biochemistry Nuclear magnetic resonance Pattern recognition Plasma temperature Principal component analysis Diseases Biomedical engineering |
| Content Type | Text |
| Resource Type | Article |
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